Loan Default Dataset EDA

Dataset statistics

Number of variables	24
Number of observations	30000
Missing cells	600
Missing cells (%)	0.1%
Duplicate rows	32
Duplicate rows (%)	0.1%
Total size in memory	5.5 MiB
Average record size in memory	192.0 B

Variable types

Numeric	14
Categorical	10

Alerts

Dataset has 32 (0.1%) duplicate rows	Duplicates
`bill_statement_sep` is highly correlated with `bill_statement_aug` and 5 other fields	High correlation
`bill_statement_aug` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`bill_statement_jul` is highly correlated with `bill_statement_sep` and 6 other fields	High correlation
`bill_statement_jun` is highly correlated with `bill_statement_sep` and 9 other fields	High correlation
`bill_statement_may` is highly correlated with `bill_statement_sep` and 9 other fields	High correlation
`bill_statement_apr` is highly correlated with `bill_statement_sep` and 8 other fields	High correlation
`previous_payment_sep` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`previous_payment_aug` is highly correlated with `bill_statement_jul` and 5 other fields	High correlation
`previous_payment_jul` is highly correlated with `bill_statement_jun` and 7 other fields	High correlation
`previous_payment_jun` is highly correlated with `bill_statement_jun` and 6 other fields	High correlation
`previous_payment_may` is highly correlated with `bill_statement_jun` and 5 other fields	High correlation
`previous_payment_apr` is highly correlated with `bill_statement_may` and 4 other fields	High correlation
`bill_statement_sep` is highly correlated with `bill_statement_aug` and 4 other fields	High correlation
`bill_statement_aug` is highly correlated with `bill_statement_sep` and 4 other fields	High correlation
`bill_statement_jul` is highly correlated with `bill_statement_sep` and 4 other fields	High correlation
`bill_statement_jun` is highly correlated with `bill_statement_sep` and 4 other fields	High correlation
`bill_statement_may` is highly correlated with `bill_statement_sep` and 4 other fields	High correlation
`bill_statement_apr` is highly correlated with `bill_statement_sep` and 4 other fields	High correlation
`bill_statement_sep` is highly correlated with `bill_statement_aug` and 4 other fields	High correlation
`bill_statement_aug` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`bill_statement_jul` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`bill_statement_jun` is highly correlated with `bill_statement_sep` and 4 other fields	High correlation
`bill_statement_may` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`bill_statement_apr` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`previous_payment_sep` is highly correlated with `bill_statement_aug`	High correlation
`previous_payment_aug` is highly correlated with `bill_statement_jul`	High correlation
`previous_payment_jun` is highly correlated with `bill_statement_may`	High correlation
`previous_payment_may` is highly correlated with `bill_statement_apr`	High correlation
`payment_status_jul` is highly correlated with `payment_status_jun` and 1 other fields	High correlation
`payment_status_sep` is highly correlated with `payment_status_aug`	High correlation
`payment_status_may` is highly correlated with `payment_status_jun` and 1 other fields	High correlation
`payment_status_jun` is highly correlated with `payment_status_jul` and 2 other fields	High correlation
`payment_status_aug` is highly correlated with `payment_status_jul` and 1 other fields	High correlation
`payment_status_apr` is highly correlated with `payment_status_may` and 1 other fields	High correlation
`limit_bal` is highly correlated with `bill_statement_sep` and 5 other fields	High correlation
`marriage` is highly correlated with `age`	High correlation
`age` is highly correlated with `marriage`	High correlation
`payment_status_sep` is highly correlated with `payment_status_aug` and 5 other fields	High correlation
`payment_status_aug` is highly correlated with `payment_status_sep` and 4 other fields	High correlation
`payment_status_jul` is highly correlated with `payment_status_sep` and 4 other fields	High correlation
`payment_status_jun` is highly correlated with `payment_status_sep` and 4 other fields	High correlation
`payment_status_may` is highly correlated with `payment_status_sep` and 4 other fields	High correlation
`payment_status_apr` is highly correlated with `payment_status_sep` and 4 other fields	High correlation
`bill_statement_sep` is highly correlated with `limit_bal` and 6 other fields	High correlation
`bill_statement_aug` is highly correlated with `limit_bal` and 6 other fields	High correlation
`bill_statement_jul` is highly correlated with `bill_statement_sep` and 6 other fields	High correlation
`bill_statement_jun` is highly correlated with `limit_bal` and 6 other fields	High correlation
`bill_statement_may` is highly correlated with `limit_bal` and 6 other fields	High correlation
`bill_statement_apr` is highly correlated with `limit_bal` and 6 other fields	High correlation
`previous_payment_sep` is highly correlated with `previous_payment_aug` and 2 other fields	High correlation
`previous_payment_aug` is highly correlated with `bill_statement_jul` and 3 other fields	High correlation
`previous_payment_jul` is highly correlated with `limit_bal` and 8 other fields	High correlation
`previous_payment_jun` is highly correlated with `previous_payment_sep` and 1 other fields	High correlation
`previous_payment_may` is highly correlated with `bill_statement_jul` and 1 other fields	High correlation
`default_payment_next_month` is highly correlated with `payment_status_sep`	High correlation
`previous_payment_aug` is highly skewed (γ1 = 30.45381745)	Skewed
`bill_statement_sep` has 2008 (6.7%) zeros	Zeros
`bill_statement_aug` has 2506 (8.4%) zeros	Zeros
`bill_statement_jul` has 2870 (9.6%) zeros	Zeros
`bill_statement_jun` has 3195 (10.7%) zeros	Zeros
`bill_statement_may` has 3506 (11.7%) zeros	Zeros
`bill_statement_apr` has 4020 (13.4%) zeros	Zeros
`previous_payment_sep` has 5249 (17.5%) zeros	Zeros
`previous_payment_aug` has 5396 (18.0%) zeros	Zeros
`previous_payment_jul` has 5968 (19.9%) zeros	Zeros
`previous_payment_jun` has 6408 (21.4%) zeros	Zeros
`previous_payment_may` has 6703 (22.3%) zeros	Zeros
`previous_payment_apr` has 7173 (23.9%) zeros	Zeros

Reproduction

Analysis started	2022-05-18 19:57:46.019866
Analysis finished	2022-05-18 19:57:59.697253
Duration	13.68 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

limit_bal
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	81
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	167484.3227

Minimum	10000
Maximum	1000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	10000
5-th percentile	20000
Q1	50000
median	140000
Q3	240000
95-th percentile	430000
Maximum	1000000
Range	990000
Interquartile range (IQR)	190000

Descriptive statistics

Standard deviation	129747.6616
Coefficient of variation (CV)	0.7746854124
Kurtosis	0.5362628964
Mean	167484.3227
Median Absolute Deviation (MAD)	90000
Skewness	0.9928669605
Sum	5024529680
Variance	1.683445568 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50000	3365	11.2%
20000	1976	6.6%
30000	1610	5.4%
80000	1567	5.2%
200000	1528	5.1%
150000	1110	3.7%
100000	1048	3.5%
180000	995	3.3%
360000	881	2.9%
60000	825	2.8%
Other values (71)	15095	50.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
10000	493	1.6%
16000	2	< 0.1%
20000	1976	6.6%
30000	1610	5.4%
40000	230	0.8%
50000	3365	11.2%
60000	825	2.8%
70000	731	2.4%
80000	1567	5.2%
90000	651	2.2%

Value	Count	Frequency (%)
1000000	1	< 0.1%
800000	2	< 0.1%
780000	2	< 0.1%
760000	1	< 0.1%
750000	4	< 0.1%
740000	2	< 0.1%
730000	2	< 0.1%
720000	3	< 0.1%
710000	6	< 0.1%
700000	8	< 0.1%

sex
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	150
Missing (%)	0.5%
Memory size	234.5 KiB

Female	18027
Male	11823

Length

Max length	6
Median length	6
Mean length	5.207839196
Min length	4

Characters and Unicode

Total characters	155454
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Female
2nd row	Female
3rd row	Female
4th row	Female
5th row	Male

Common Values

Value	Count	Frequency (%)
Female	18027	60.1%
Male	11823	39.4%
(Missing)	150	0.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
female	18027	60.4%
male	11823	39.6%

Most occurring characters

Value	Count	Frequency (%)
e	47877	30.8%
a	29850	19.2%
l	29850	19.2%
F	18027	11.6%
m	18027	11.6%
M	11823	7.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	125604	80.8%
Uppercase Letter	29850	19.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	47877	38.1%
a	29850	23.8%
l	29850	23.8%
m	18027	14.4%

Uppercase Letter

Value	Count	Frequency (%)
F	18027	60.4%
M	11823	39.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	155454	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	47877	30.8%
a	29850	19.2%
l	29850	19.2%
F	18027	11.6%
m	18027	11.6%
M	11823	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	155454	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	47877	30.8%
a	29850	19.2%
l	29850	19.2%
F	18027	11.6%
m	18027	11.6%
M	11823	7.6%

education
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	150
Missing (%)	0.5%
Memory size	234.5 KiB

University	13960
Graduate school	10537
High school	4886
Others	467

Length

Max length	15
Median length	11
Mean length	11.86609715
Min length	6

Characters and Unicode

Total characters	354203
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	University
2nd row	University
3rd row	University
4th row	University
5th row	University

Common Values

Value	Count	Frequency (%)
University	13960	46.5%
Graduate school	10537	35.1%
High school	4886	16.3%
Others	467	1.6%
(Missing)	150	0.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
school	15423	34.1%
university	13960	30.8%
graduate	10537	23.3%
high	4886	10.8%
others	467	1.0%

Most occurring characters

Value	Count	Frequency (%)
i	32806	9.3%
o	30846	8.7%
s	29850	8.4%
e	24964	7.0%
r	24964	7.0%
t	24964	7.0%
a	21074	5.9%
h	20776	5.9%
	15423	4.4%
l	15423	4.4%
Other values (11)	113113	31.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	308930	87.2%
Uppercase Letter	29850	8.4%
Space Separator	15423	4.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	32806	10.6%
o	30846	10.0%
s	29850	9.7%
e	24964	8.1%
r	24964	8.1%
t	24964	8.1%
a	21074	6.8%
h	20776	6.7%
l	15423	5.0%
c	15423	5.0%
Other values (6)	67840	22.0%

Uppercase Letter

Value	Count	Frequency (%)
U	13960	46.8%
G	10537	35.3%
H	4886	16.4%
O	467	1.6%

Space Separator

Value	Count	Frequency (%)
	15423	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	338780	95.6%
Common	15423	4.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	32806	9.7%
o	30846	9.1%
s	29850	8.8%
e	24964	7.4%
r	24964	7.4%
t	24964	7.4%
a	21074	6.2%
h	20776	6.1%
l	15423	4.6%
c	15423	4.6%
Other values (10)	97690	28.8%

Common

Value	Count	Frequency (%)
	15423	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	354203	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	32806	9.3%
o	30846	8.7%
s	29850	8.4%
e	24964	7.0%
r	24964	7.0%
t	24964	7.0%
a	21074	5.9%
h	20776	5.9%
	15423	4.4%
l	15423	4.4%
Other values (11)	113113	31.9%

marriage
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	150
Missing (%)	0.5%
Memory size	234.5 KiB

Single	15891
Married	13585
Others	374

Length

Max length	7
Median length	6
Mean length	6.455108878
Min length	6

Characters and Unicode

Total characters	192685
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Married
2nd row	Single
3rd row	Single
4th row	Married
5th row	Married

Common Values

Value	Count	Frequency (%)
Single	15891	53.0%
Married	13585	45.3%
Others	374	1.2%
(Missing)	150	0.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
single	15891	53.2%
married	13585	45.5%
others	374	1.3%

Most occurring characters

Value	Count	Frequency (%)
e	29850	15.5%
i	29476	15.3%
r	27544	14.3%
S	15891	8.2%
n	15891	8.2%
g	15891	8.2%
l	15891	8.2%
M	13585	7.1%
a	13585	7.1%
d	13585	7.1%
Other values (4)	1496	0.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	162835	84.5%
Uppercase Letter	29850	15.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	29850	18.3%
i	29476	18.1%
r	27544	16.9%
n	15891	9.8%
g	15891	9.8%
l	15891	9.8%
a	13585	8.3%
d	13585	8.3%
t	374	0.2%
h	374	0.2%

Uppercase Letter

Value	Count	Frequency (%)
S	15891	53.2%
M	13585	45.5%
O	374	1.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	192685	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	29850	15.5%
i	29476	15.3%
r	27544	14.3%
S	15891	8.2%
n	15891	8.2%
g	15891	8.2%
l	15891	8.2%
M	13585	7.1%
a	13585	7.1%
d	13585	7.1%
Other values (4)	1496	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	192685	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	29850	15.5%
i	29476	15.3%
r	27544	14.3%
S	15891	8.2%
n	15891	8.2%
g	15891	8.2%
l	15891	8.2%
M	13585	7.1%
a	13585	7.1%
d	13585	7.1%
Other values (4)	1496	0.8%

age
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	56
Distinct (%)	0.2%
Missing	150
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	35.49011725

Minimum	21
Maximum	79
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	21
5-th percentile	23
Q1	28
median	34
Q3	41
95-th percentile	53
Maximum	79
Range	58
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	9.217852014
Coefficient of variation (CV)	0.2597301088
Kurtosis	0.04642546306
Mean	35.49011725
Median Absolute Deviation (MAD)	6
Skewness	0.7324726269
Sum	1059380
Variance	84.96879576
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
29	1602	5.3%
27	1470	4.9%
28	1402	4.7%
30	1388	4.6%
26	1246	4.2%
31	1208	4.0%
25	1180	3.9%
32	1156	3.9%
34	1154	3.8%
33	1139	3.8%
Other values (46)	16905	56.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
21	66	0.2%
22	558	1.9%
23	922	3.1%
24	1120	3.7%
25	1180	3.9%
26	1246	4.2%
27	1470	4.9%
28	1402	4.7%
29	1602	5.3%
30	1388	4.6%

Value	Count	Frequency (%)
79	1	< 0.1%
75	3	< 0.1%
74	1	< 0.1%
73	4	< 0.1%
72	3	< 0.1%
71	3	< 0.1%
70	10	< 0.1%
69	15	0.1%
68	5	< 0.1%
67	16	0.1%

payment_status_sep
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Unknown	17496
Payed duly	5686
Payment delayed 1 month	3688
Payment delayed 2 months	2667
Payment delayed 3 months	322
Other values (5)	141

Length

Max length	24
Median length	7
Mean length	11.3092
Min length	7

Characters and Unicode

Total characters	339276
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Payment delayed 2 months
2nd row	Payed duly
3rd row	Unknown
4th row	Unknown
5th row	Payed duly

Common Values

Value	Count	Frequency (%)
Unknown	17496	58.3%
Payed duly	5686	19.0%
Payment delayed 1 month	3688	12.3%
Payment delayed 2 months	2667	8.9%
Payment delayed 3 months	322	1.1%
Payment delayed 4 months	76	0.3%
Payment delayed 5 months	26	0.1%
Payment delayed 8 months	19	0.1%
Payment delayed 6 months	11	< 0.1%
Payment delayed 7 months	9	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
unknown	17496	31.2%
payment	6818	12.1%
delayed	6818	12.1%
payed	5686	10.1%
duly	5686	10.1%
1	3688	6.6%
month	3688	6.6%
months	3130	5.6%
2	2667	4.8%
3	322	0.6%
Other values (5)	141	0.3%

Most occurring characters

Value	Count	Frequency (%)
n	66124	19.5%
e	26140	7.7%
	26140	7.7%
y	25008	7.4%
d	25008	7.4%
o	24314	7.2%
a	19322	5.7%
U	17496	5.2%
k	17496	5.2%
w	17496	5.2%
Other values (15)	74732	22.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	276318	81.4%
Uppercase Letter	30000	8.8%
Space Separator	26140	7.7%
Decimal Number	6818	2.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	66124	23.9%
e	26140	9.5%
y	25008	9.1%
d	25008	9.1%
o	24314	8.8%
a	19322	7.0%
k	17496	6.3%
w	17496	6.3%
t	13636	4.9%
m	13636	4.9%
Other values (4)	28138	10.2%

Decimal Number

Value	Count	Frequency (%)
1	3688	54.1%
2	2667	39.1%
3	322	4.7%
4	76	1.1%
5	26	0.4%
8	19	0.3%
6	11	0.2%
7	9	0.1%

Uppercase Letter

Value	Count	Frequency (%)
U	17496	58.3%
P	12504	41.7%

Space Separator

Value	Count	Frequency (%)
	26140	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	306318	90.3%
Common	32958	9.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	66124	21.6%
e	26140	8.5%
y	25008	8.2%
d	25008	8.2%
o	24314	7.9%
a	19322	6.3%
U	17496	5.7%
k	17496	5.7%
w	17496	5.7%
t	13636	4.5%
Other values (6)	54278	17.7%

Common

Value	Count	Frequency (%)
	26140	79.3%
1	3688	11.2%
2	2667	8.1%
3	322	1.0%
4	76	0.2%
5	26	0.1%
8	19	0.1%
6	11	< 0.1%
7	9	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	339276	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	66124	19.5%
e	26140	7.7%
	26140	7.7%
y	25008	7.4%
d	25008	7.4%
o	24314	7.2%
a	19322	5.7%
U	17496	5.2%
k	17496	5.2%
w	17496	5.2%
Other values (15)	74732	22.0%

payment_status_aug
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Unknown	19512
Payed duly	6050
Payment delayed 2 months	3927
Payment delayed 3 months	326
Payment delayed 4 months	99
Other values (5)	86

Length

Max length	24
Median length	7
Mean length	10.11893333
Min length	7

Characters and Unicode

Total characters	303568
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Payment delayed 2 months
2nd row	Payment delayed 2 months
3rd row	Unknown
4th row	Unknown
5th row	Unknown

Common Values

Value	Count	Frequency (%)
Unknown	19512	65.0%
Payed duly	6050	20.2%
Payment delayed 2 months	3927	13.1%
Payment delayed 3 months	326	1.1%
Payment delayed 4 months	99	0.3%
Payment delayed 1 month	28	0.1%
Payment delayed 5 months	25	0.1%
Payment delayed 7 months	20	0.1%
Payment delayed 6 months	12	< 0.1%
Payment delayed 8 months	1	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
unknown	19512	39.5%
payed	6050	12.3%
duly	6050	12.3%
payment	4438	9.0%
delayed	4438	9.0%
months	4410	8.9%
2	3927	8.0%
3	326	0.7%
4	99	0.2%
1	28	0.1%
Other values (5)	86	0.2%

Most occurring characters

Value	Count	Frequency (%)
n	67412	22.2%
o	23950	7.9%
y	20976	6.9%
d	20976	6.9%
U	19512	6.4%
k	19512	6.4%
w	19512	6.4%
	19364	6.4%
e	19364	6.4%
a	14926	4.9%
Other values (15)	58064	19.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	249766	82.3%
Uppercase Letter	30000	9.9%
Space Separator	19364	6.4%
Decimal Number	4438	1.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	67412	27.0%
o	23950	9.6%
y	20976	8.4%
d	20976	8.4%
k	19512	7.8%
w	19512	7.8%
e	19364	7.8%
a	14926	6.0%
l	10488	4.2%
m	8876	3.6%
Other values (4)	23774	9.5%

Decimal Number

Value	Count	Frequency (%)
2	3927	88.5%
3	326	7.3%
4	99	2.2%
1	28	0.6%
5	25	0.6%
7	20	0.5%
6	12	0.3%
8	1	< 0.1%

Uppercase Letter

Value	Count	Frequency (%)
U	19512	65.0%
P	10488	35.0%

Space Separator

Value	Count	Frequency (%)
	19364	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	279766	92.2%
Common	23802	7.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	67412	24.1%
o	23950	8.6%
y	20976	7.5%
d	20976	7.5%
U	19512	7.0%
k	19512	7.0%
w	19512	7.0%
e	19364	6.9%
a	14926	5.3%
l	10488	3.7%
Other values (6)	43138	15.4%

Common

Value	Count	Frequency (%)
	19364	81.4%
2	3927	16.5%
3	326	1.4%
4	99	0.4%
1	28	0.1%
5	25	0.1%
7	20	0.1%
6	12	0.1%
8	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	303568	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	67412	22.2%
o	23950	7.9%
y	20976	6.9%
d	20976	6.9%
U	19512	6.4%
k	19512	6.4%
w	19512	6.4%
	19364	6.4%
e	19364	6.4%
a	14926	4.9%
Other values (15)	58064	19.1%

payment_status_jul
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Unknown	19849
Payed duly	5938
Payment delayed 2 months	3819
Payment delayed 3 months	240
Payment delayed 4 months	76
Other values (5)	78

Length

Max length	24
Median length	7
Mean length	9.981033333
Min length	7

Characters and Unicode

Total characters	299431
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Payed duly
2nd row	Unknown
3rd row	Unknown
4th row	Unknown
5th row	Payed duly

Common Values

Value	Count	Frequency (%)
Unknown	19849	66.2%
Payed duly	5938	19.8%
Payment delayed 2 months	3819	12.7%
Payment delayed 3 months	240	0.8%
Payment delayed 4 months	76	0.3%
Payment delayed 7 months	27	0.1%
Payment delayed 6 months	23	0.1%
Payment delayed 5 months	21	0.1%
Payment delayed 1 month	4	< 0.1%
Payment delayed 8 months	3	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
unknown	19849	40.9%
payed	5938	12.2%
duly	5938	12.2%
payment	4213	8.7%
delayed	4213	8.7%
months	4209	8.7%
2	3819	7.9%
3	240	0.5%
4	76	0.2%
7	27	0.1%
Other values (5)	55	0.1%

Most occurring characters

Value	Count	Frequency (%)
n	67973	22.7%
o	24062	8.0%
y	20302	6.8%
d	20302	6.8%
U	19849	6.6%
k	19849	6.6%
w	19849	6.6%
	18577	6.2%
e	18577	6.2%
a	14364	4.8%
Other values (15)	55727	18.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	246641	82.4%
Uppercase Letter	30000	10.0%
Space Separator	18577	6.2%
Decimal Number	4213	1.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	67973	27.6%
o	24062	9.8%
y	20302	8.2%
d	20302	8.2%
k	19849	8.0%
w	19849	8.0%
e	18577	7.5%
a	14364	5.8%
l	10151	4.1%
m	8426	3.4%
Other values (4)	22786	9.2%

Decimal Number

Value	Count	Frequency (%)
2	3819	90.6%
3	240	5.7%
4	76	1.8%
7	27	0.6%
6	23	0.5%
5	21	0.5%
1	4	0.1%
8	3	0.1%

Uppercase Letter

Value	Count	Frequency (%)
U	19849	66.2%
P	10151	33.8%

Space Separator

Value	Count	Frequency (%)
	18577	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	276641	92.4%
Common	22790	7.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	67973	24.6%
o	24062	8.7%
y	20302	7.3%
d	20302	7.3%
U	19849	7.2%
k	19849	7.2%
w	19849	7.2%
e	18577	6.7%
a	14364	5.2%
l	10151	3.7%
Other values (6)	41363	15.0%

Common

Value	Count	Frequency (%)
	18577	81.5%
2	3819	16.8%
3	240	1.1%
4	76	0.3%
7	27	0.1%
6	23	0.1%
5	21	0.1%
1	4	< 0.1%
8	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	299431	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	67973	22.7%
o	24062	8.0%
y	20302	6.8%
d	20302	6.8%
U	19849	6.6%
k	19849	6.6%
w	19849	6.6%
	18577	6.2%
e	18577	6.2%
a	14364	4.8%
Other values (15)	55727	18.6%

payment_status_jun
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Unknown	20803
Payed duly	5687
Payment delayed 2 months	3159
Payment delayed 3 months	180
Payment delayed 4 months	69
Other values (5)	102

Length

Max length	24
Median length	7
Mean length	9.557633333
Min length	7

Characters and Unicode

Total characters	286729
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Payed duly
2nd row	Unknown
3rd row	Unknown
4th row	Unknown
5th row	Unknown

Common Values

Value	Count	Frequency (%)
Unknown	20803	69.3%
Payed duly	5687	19.0%
Payment delayed 2 months	3159	10.5%
Payment delayed 3 months	180	0.6%
Payment delayed 4 months	69	0.2%
Payment delayed 7 months	58	0.2%
Payment delayed 5 months	35	0.1%
Payment delayed 6 months	5	< 0.1%
Payment delayed 8 months	2	< 0.1%
Payment delayed 1 month	2	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
unknown	20803	45.0%
payed	5687	12.3%
duly	5687	12.3%
payment	3510	7.6%
delayed	3510	7.6%
months	3508	7.6%
2	3159	6.8%
3	180	0.4%
4	69	0.1%
7	58	0.1%
Other values (5)	46	0.1%

Most occurring characters

Value	Count	Frequency (%)
n	69429	24.2%
o	24313	8.5%
U	20803	7.3%
k	20803	7.3%
w	20803	7.3%
y	18394	6.4%
d	18394	6.4%
	16217	5.7%
e	16217	5.7%
a	12707	4.4%
Other values (15)	48649	17.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	237002	82.7%
Uppercase Letter	30000	10.5%
Space Separator	16217	5.7%
Decimal Number	3510	1.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	69429	29.3%
o	24313	10.3%
k	20803	8.8%
w	20803	8.8%
y	18394	7.8%
d	18394	7.8%
e	16217	6.8%
a	12707	5.4%
l	9197	3.9%
m	7020	3.0%
Other values (4)	19725	8.3%

Decimal Number

Value	Count	Frequency (%)
2	3159	90.0%
3	180	5.1%
4	69	2.0%
7	58	1.7%
5	35	1.0%
6	5	0.1%
8	2	0.1%
1	2	0.1%

Uppercase Letter

Value	Count	Frequency (%)
U	20803	69.3%
P	9197	30.7%

Space Separator

Value	Count	Frequency (%)
	16217	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	267002	93.1%
Common	19727	6.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	69429	26.0%
o	24313	9.1%
U	20803	7.8%
k	20803	7.8%
w	20803	7.8%
y	18394	6.9%
d	18394	6.9%
e	16217	6.1%
a	12707	4.8%
l	9197	3.4%
Other values (6)	35942	13.5%

Common

Value	Count	Frequency (%)
	16217	82.2%
2	3159	16.0%
3	180	0.9%
4	69	0.3%
7	58	0.3%
5	35	0.2%
6	5	< 0.1%
8	2	< 0.1%
1	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	286729	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	69429	24.2%
o	24313	8.5%
U	20803	7.3%
k	20803	7.3%
w	20803	7.3%
y	18394	6.4%
d	18394	6.4%
	16217	5.7%
e	16217	5.7%
a	12707	4.4%
Other values (15)	48649	17.0%

payment_status_may
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Unknown	21493
Payed duly	5539
Payment delayed 2 months	2626
Payment delayed 3 months	178
Payment delayed 4 months	84
Other values (4)	80

Length

Max length	24
Median length	7
Mean length	9.235766667
Min length	7

Characters and Unicode

Total characters	277073
Distinct characters	24
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Unknown
2nd row	Unknown
3rd row	Unknown
4th row	Unknown
5th row	Unknown

Common Values

Value	Count	Frequency (%)
Unknown	21493	71.6%
Payed duly	5539	18.5%
Payment delayed 2 months	2626	8.8%
Payment delayed 3 months	178	0.6%
Payment delayed 4 months	84	0.3%
Payment delayed 7 months	58	0.2%
Payment delayed 5 months	17	0.1%
Payment delayed 6 months	4	< 0.1%
Payment delayed 8 months	1	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
unknown	21493	48.4%
payed	5539	12.5%
duly	5539	12.5%
payment	2968	6.7%
delayed	2968	6.7%
months	2968	6.7%
2	2626	5.9%
3	178	0.4%
4	84	0.2%
7	58	0.1%
Other values (3)	22	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
n	70415	25.4%
o	24461	8.8%
U	21493	7.8%
k	21493	7.8%
w	21493	7.8%
y	17014	6.1%
d	17014	6.1%
	14443	5.2%
e	14443	5.2%
a	11475	4.1%
Other values (14)	43329	15.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	229662	82.9%
Uppercase Letter	30000	10.8%
Space Separator	14443	5.2%
Decimal Number	2968	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	70415	30.7%
o	24461	10.7%
k	21493	9.4%
w	21493	9.4%
y	17014	7.4%
d	17014	7.4%
e	14443	6.3%
a	11475	5.0%
l	8507	3.7%
m	5936	2.6%
Other values (4)	17411	7.6%

Decimal Number

Value	Count	Frequency (%)
2	2626	88.5%
3	178	6.0%
4	84	2.8%
7	58	2.0%
5	17	0.6%
6	4	0.1%
8	1	< 0.1%

Uppercase Letter

Value	Count	Frequency (%)
U	21493	71.6%
P	8507	28.4%

Space Separator

Value	Count	Frequency (%)
	14443	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	259662	93.7%
Common	17411	6.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	70415	27.1%
o	24461	9.4%
U	21493	8.3%
k	21493	8.3%
w	21493	8.3%
y	17014	6.6%
d	17014	6.6%
e	14443	5.6%
a	11475	4.4%
l	8507	3.3%
Other values (6)	31854	12.3%

Common

Value	Count	Frequency (%)
	14443	83.0%
2	2626	15.1%
3	178	1.0%
4	84	0.5%
7	58	0.3%
5	17	0.1%
6	4	< 0.1%
8	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	277073	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	70415	25.4%
o	24461	8.8%
U	21493	7.8%
k	21493	7.8%
w	21493	7.8%
y	17014	6.1%
d	17014	6.1%
	14443	5.2%
e	14443	5.2%
a	11475	4.1%
Other values (14)	43329	15.6%

payment_status_apr
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Unknown	21181
Payed duly	5740
Payment delayed 2 months	2766
Payment delayed 3 months	184
Payment delayed 4 months	49
Other values (4)	80

Length

Max length	24
Median length	7
Mean length	9.318766667
Min length	7

Characters and Unicode

Total characters	279563
Distinct characters	24
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Unknown
2nd row	Payment delayed 2 months
3rd row	Unknown
4th row	Unknown
5th row	Unknown

Common Values

Value	Count	Frequency (%)
Unknown	21181	70.6%
Payed duly	5740	19.1%
Payment delayed 2 months	2766	9.2%
Payment delayed 3 months	184	0.6%
Payment delayed 4 months	49	0.2%
Payment delayed 7 months	46	0.2%
Payment delayed 6 months	19	0.1%
Payment delayed 5 months	13	< 0.1%
Payment delayed 8 months	2	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
unknown	21181	47.1%
payed	5740	12.8%
duly	5740	12.8%
payment	3079	6.8%
delayed	3079	6.8%
months	3079	6.8%
2	2766	6.1%
3	184	0.4%
4	49	0.1%
7	46	0.1%
Other values (3)	34	0.1%

Most occurring characters

Value	Count	Frequency (%)
n	69701	24.9%
o	24260	8.7%
U	21181	7.6%
k	21181	7.6%
w	21181	7.6%
y	17638	6.3%
d	17638	6.3%
	14977	5.4%
e	14977	5.4%
a	11898	4.3%
Other values (14)	44931	16.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	231507	82.8%
Uppercase Letter	30000	10.7%
Space Separator	14977	5.4%
Decimal Number	3079	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	69701	30.1%
o	24260	10.5%
k	21181	9.1%
w	21181	9.1%
y	17638	7.6%
d	17638	7.6%
e	14977	6.5%
a	11898	5.1%
l	8819	3.8%
m	6158	2.7%
Other values (4)	18056	7.8%

Decimal Number

Value	Count	Frequency (%)
2	2766	89.8%
3	184	6.0%
4	49	1.6%
7	46	1.5%
6	19	0.6%
5	13	0.4%
8	2	0.1%

Uppercase Letter

Value	Count	Frequency (%)
U	21181	70.6%
P	8819	29.4%

Space Separator

Value	Count	Frequency (%)
	14977	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	261507	93.5%
Common	18056	6.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	69701	26.7%
o	24260	9.3%
U	21181	8.1%
k	21181	8.1%
w	21181	8.1%
y	17638	6.7%
d	17638	6.7%
e	14977	5.7%
a	11898	4.5%
l	8819	3.4%
Other values (6)	33033	12.6%

Common

Value	Count	Frequency (%)
	14977	82.9%
2	2766	15.3%
3	184	1.0%
4	49	0.3%
7	46	0.3%
6	19	0.1%
5	13	0.1%
8	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	279563	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	69701	24.9%
o	24260	8.7%
U	21181	7.6%
k	21181	7.6%
w	21181	7.6%
y	17638	6.3%
d	17638	6.3%
	14977	5.4%
e	14977	5.4%
a	11898	4.3%
Other values (14)	44931	16.1%

bill_statement_sep
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	22723
Distinct (%)	75.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	51223.3309

Minimum	-165580
Maximum	964511
Zeros	2008
Zeros (%)	6.7%
Negative	590
Negative (%)	2.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	-165580
5-th percentile	0
Q1	3558.75
median	22381.5
Q3	67091
95-th percentile	201203.05
Maximum	964511
Range	1130091
Interquartile range (IQR)	63532.25

Descriptive statistics

Standard deviation	73635.86058
Coefficient of variation (CV)	1.437545339
Kurtosis	9.806289341
Mean	51223.3309
Median Absolute Deviation (MAD)	21800.5
Skewness	2.663861022
Sum	1536699927
Variance	5422239963
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2008	6.7%
390	244	0.8%
780	76	0.3%
326	72	0.2%
316	63	0.2%
2500	59	0.2%
396	49	0.2%
2400	39	0.1%
416	29	0.1%
500	25	0.1%
Other values (22713)	27336	91.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-165580	1	< 0.1%
-154973	1	< 0.1%
-15308	1	< 0.1%
-14386	1	< 0.1%
-11545	1	< 0.1%
-10682	1	< 0.1%
-9802	1	< 0.1%
-9095	1	< 0.1%
-8187	1	< 0.1%
-7438	1	< 0.1%

Value	Count	Frequency (%)
964511	1	< 0.1%
746814	1	< 0.1%
653062	1	< 0.1%
630458	1	< 0.1%
626648	1	< 0.1%
621749	1	< 0.1%
613860	1	< 0.1%
610723	1	< 0.1%
608594	1	< 0.1%
604019	1	< 0.1%

bill_statement_aug
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	22346
Distinct (%)	74.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49179.07517

Minimum	-69777
Maximum	983931
Zeros	2506
Zeros (%)	8.4%
Negative	669
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-69777
5-th percentile	0
Q1	2984.75
median	21200
Q3	64006.25
95-th percentile	194792.2
Maximum	983931
Range	1053708
Interquartile range (IQR)	61021.5

Descriptive statistics

Standard deviation	71173.76878
Coefficient of variation (CV)	1.447236829
Kurtosis	10.30294592
Mean	49179.07517
Median Absolute Deviation (MAD)	20810
Skewness	2.705220853
Sum	1475372255
Variance	5065705363
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2506	8.4%
390	231	0.8%
326	75	0.2%
780	75	0.2%
316	72	0.2%
396	51	0.2%
2500	51	0.2%
2400	42	0.1%
-200	29	0.1%
416	28	0.1%
Other values (22336)	26840	89.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-69777	1	< 0.1%
-67526	1	< 0.1%
-33350	1	< 0.1%
-30000	1	< 0.1%
-26214	1	< 0.1%
-24704	1	< 0.1%
-24702	1	< 0.1%
-22960	1	< 0.1%
-18618	1	< 0.1%
-18088	1	< 0.1%

Value	Count	Frequency (%)
983931	1	< 0.1%
743970	1	< 0.1%
671563	1	< 0.1%
646770	1	< 0.1%
624475	1	< 0.1%
605943	1	< 0.1%
597793	1	< 0.1%
586825	1	< 0.1%
581775	1	< 0.1%
577681	1	< 0.1%

bill_statement_jul
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	22026
Distinct (%)	73.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	47013.1548

Minimum	-157264
Maximum	1664089
Zeros	2870
Zeros (%)	9.6%
Negative	655
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-157264
5-th percentile	0
Q1	2666.25
median	20088.5
Q3	60164.75
95-th percentile	187821.05
Maximum	1664089
Range	1821353
Interquartile range (IQR)	57498.5

Descriptive statistics

Standard deviation	69349.38743
Coefficient of variation (CV)	1.475106015
Kurtosis	19.78325514
Mean	47013.1548
Median Absolute Deviation (MAD)	19708.5
Skewness	3.087830046
Sum	1410394644
Variance	4809337537
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2870	9.6%
390	275	0.9%
780	74	0.2%
326	63	0.2%
316	62	0.2%
396	48	0.2%
2500	40	0.1%
2400	39	0.1%
416	29	0.1%
200	27	0.1%
Other values (22016)	26473	88.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-157264	1	< 0.1%
-61506	1	< 0.1%
-46127	1	< 0.1%
-34041	1	< 0.1%
-25443	1	< 0.1%
-24702	1	< 0.1%
-20320	1	< 0.1%
-17706	1	< 0.1%
-15910	1	< 0.1%
-15641	1	< 0.1%

Value	Count	Frequency (%)
1664089	1	< 0.1%
855086	1	< 0.1%
693131	1	< 0.1%
689643	1	< 0.1%
689627	1	< 0.1%
632041	1	< 0.1%
597415	1	< 0.1%
578971	1	< 0.1%
577957	1	< 0.1%
577015	1	< 0.1%

bill_statement_jun
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	21548
Distinct (%)	71.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	43262.94897

Minimum	-170000
Maximum	891586
Zeros	3195
Zeros (%)	10.7%
Negative	675
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-170000
5-th percentile	0
Q1	2326.75
median	19052
Q3	54506
95-th percentile	174333.35
Maximum	891586
Range	1061586
Interquartile range (IQR)	52179.25

Descriptive statistics

Standard deviation	64332.85613
Coefficient of variation (CV)	1.487019671
Kurtosis	11.30932483
Mean	43262.94897
Median Absolute Deviation (MAD)	18656
Skewness	2.821965291
Sum	1297888469
Variance	4138716378
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3195	10.7%
390	246	0.8%
780	101	0.3%
316	68	0.2%
326	62	0.2%
396	44	0.1%
2400	39	0.1%
150	39	0.1%
2500	34	0.1%
416	33	0.1%
Other values (21538)	26139	87.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-170000	1	< 0.1%
-81334	1	< 0.1%
-65167	1	< 0.1%
-50616	1	< 0.1%
-46627	1	< 0.1%
-34503	1	< 0.1%
-27490	1	< 0.1%
-24303	1	< 0.1%
-22108	1	< 0.1%
-20320	1	< 0.1%

Value	Count	Frequency (%)
891586	1	< 0.1%
706864	1	< 0.1%
628699	1	< 0.1%
616836	1	< 0.1%
572805	1	< 0.1%
569034	1	< 0.1%
565669	1	< 0.1%
563543	1	< 0.1%
548020	1	< 0.1%
542653	1	< 0.1%

bill_statement_may
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	21010
Distinct (%)	70.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	40311.40097

Minimum	-81334
Maximum	927171
Zeros	3506
Zeros (%)	11.7%
Negative	655
Negative (%)	2.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-81334
5-th percentile	0
Q1	1763
median	18104.5
Q3	50190.5
95-th percentile	165794.3
Maximum	927171
Range	1008505
Interquartile range (IQR)	48427.5

Descriptive statistics

Standard deviation	60797.15577
Coefficient of variation (CV)	1.508187617
Kurtosis	12.30588129
Mean	40311.40097
Median Absolute Deviation (MAD)	17688.5
Skewness	2.876379867
Sum	1209342029
Variance	3696294150
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3506	11.7%
390	235	0.8%
780	94	0.3%
316	79	0.3%
326	62	0.2%
150	58	0.2%
396	47	0.2%
2400	39	0.1%
2500	37	0.1%
416	36	0.1%
Other values (21000)	25807	86.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-81334	1	< 0.1%
-61372	1	< 0.1%
-53007	1	< 0.1%
-46627	1	< 0.1%
-37594	1	< 0.1%
-36156	1	< 0.1%
-30481	1	< 0.1%
-28335	1	< 0.1%
-23003	1	< 0.1%
-20753	1	< 0.1%

Value	Count	Frequency (%)
927171	1	< 0.1%
823540	1	< 0.1%
587067	1	< 0.1%
551702	1	< 0.1%
547880	1	< 0.1%
530672	1	< 0.1%
524315	1	< 0.1%
516139	1	< 0.1%
514114	1	< 0.1%
508213	1	< 0.1%

bill_statement_apr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	20604
Distinct (%)	68.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38871.7604

Minimum	-339603
Maximum	961664
Zeros	4020
Zeros (%)	13.4%
Negative	688
Negative (%)	2.3%
Memory size	234.5 KiB

Quantile statistics

Minimum	-339603
5-th percentile	0
Q1	1256
median	17071
Q3	49198.25
95-th percentile	161912
Maximum	961664
Range	1301267
Interquartile range (IQR)	47942.25

Descriptive statistics

Standard deviation	59554.10754
Coefficient of variation (CV)	1.53206613
Kurtosis	12.27070529
Mean	38871.7604
Median Absolute Deviation (MAD)	16755
Skewness	2.846644576
Sum	1166152812
Variance	3546691724
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4020	13.4%
390	207	0.7%
780	86	0.3%
150	78	0.3%
316	77	0.3%
326	56	0.2%
396	45	0.1%
416	36	0.1%
-18	33	0.1%
2400	32	0.1%
Other values (20594)	25330	84.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-339603	1	< 0.1%
-209051	1	< 0.1%
-150953	1	< 0.1%
-94625	1	< 0.1%
-73895	1	< 0.1%
-57060	1	< 0.1%
-51443	1	< 0.1%
-51183	1	< 0.1%
-46627	1	< 0.1%
-45734	1	< 0.1%

Value	Count	Frequency (%)
961664	1	< 0.1%
699944	1	< 0.1%
568638	1	< 0.1%
527711	1	< 0.1%
527566	1	< 0.1%
514975	1	< 0.1%
513798	1	< 0.1%
511905	1	< 0.1%
501370	1	< 0.1%
499100	1	< 0.1%

previous_payment_sep
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7943
Distinct (%)	26.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5663.5805

Minimum	0
Maximum	873552
Zeros	5249
Zeros (%)	17.5%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1000
median	2100
Q3	5006
95-th percentile	18428.2
Maximum	873552
Range	873552
Interquartile range (IQR)	4006

Descriptive statistics

Standard deviation	16563.28035
Coefficient of variation (CV)	2.924524575
Kurtosis	415.2547427
Mean	5663.5805
Median Absolute Deviation (MAD)	1932
Skewness	14.66836433
Sum	169907415
Variance	274342256.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5249	17.5%
2000	1363	4.5%
3000	891	3.0%
5000	698	2.3%
1500	507	1.7%
4000	426	1.4%
10000	401	1.3%
1000	365	1.2%
2500	298	1.0%
6000	294	1.0%
Other values (7933)	19508	65.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	5249	17.5%
1	9	< 0.1%
2	14	< 0.1%
3	15	0.1%
4	18	0.1%
5	12	< 0.1%
6	15	0.1%
7	9	< 0.1%
8	8	< 0.1%
9	7	< 0.1%

Value	Count	Frequency (%)
873552	1	< 0.1%
505000	1	< 0.1%
493358	1	< 0.1%
423903	1	< 0.1%
405016	1	< 0.1%
368199	1	< 0.1%
323014	1	< 0.1%
304815	1	< 0.1%
302000	1	< 0.1%
300039	1	< 0.1%

previous_payment_aug
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	7899
Distinct (%)	26.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5921.1635

Minimum	0
Maximum	1684259
Zeros	5396
Zeros (%)	18.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	833
median	2009
Q3	5000
95-th percentile	19004.35
Maximum	1684259
Range	1684259
Interquartile range (IQR)	4167

Descriptive statistics

Standard deviation	23040.8704
Coefficient of variation (CV)	3.891274139
Kurtosis	1641.631911
Mean	5921.1635
Median Absolute Deviation (MAD)	1991
Skewness	30.45381745
Sum	177634905
Variance	530881708.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5396	18.0%
2000	1290	4.3%
3000	857	2.9%
5000	717	2.4%
1000	594	2.0%
1500	521	1.7%
4000	410	1.4%
10000	318	1.1%
6000	283	0.9%
2500	251	0.8%
Other values (7889)	19363	64.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	5396	18.0%
1	15	0.1%
2	20	0.1%
3	18	0.1%
4	11	< 0.1%
5	25	0.1%
6	8	< 0.1%
7	12	< 0.1%
8	9	< 0.1%
9	6	< 0.1%

Value	Count	Frequency (%)
1684259	1	< 0.1%
1227082	1	< 0.1%
1215471	1	< 0.1%
1024516	1	< 0.1%
580464	1	< 0.1%
415552	1	< 0.1%
401003	1	< 0.1%
388126	1	< 0.1%
385228	1	< 0.1%
384986	1	< 0.1%

previous_payment_jul
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7518
Distinct (%)	25.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5225.6815

Minimum	0
Maximum	896040
Zeros	5968
Zeros (%)	19.9%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	390
median	1800
Q3	4505
95-th percentile	17589.4
Maximum	896040
Range	896040
Interquartile range (IQR)	4115

Descriptive statistics

Standard deviation	17606.96147
Coefficient of variation (CV)	3.36931393
Kurtosis	564.3112295
Mean	5225.6815
Median Absolute Deviation (MAD)	1795
Skewness	17.21663544
Sum	156770445
Variance	310005092.2
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5968	19.9%
2000	1285	4.3%
1000	1103	3.7%
3000	870	2.9%
5000	721	2.4%
1500	490	1.6%
4000	381	1.3%
10000	312	1.0%
1200	243	0.8%
6000	241	0.8%
Other values (7508)	18386	61.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	5968	19.9%
1	13	< 0.1%
2	19	0.1%
3	14	< 0.1%
4	15	0.1%
5	18	0.1%
6	14	< 0.1%
7	18	0.1%
8	10	< 0.1%
9	12	< 0.1%

Value	Count	Frequency (%)
896040	1	< 0.1%
889043	1	< 0.1%
508229	1	< 0.1%
417588	1	< 0.1%
400972	1	< 0.1%
397092	1	< 0.1%
380478	1	< 0.1%
371718	1	< 0.1%
349395	1	< 0.1%
344261	1	< 0.1%

previous_payment_jun
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6937
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4826.076867

Minimum	0
Maximum	621000
Zeros	6408
Zeros (%)	21.4%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	296
median	1500
Q3	4013.25
95-th percentile	16014.95
Maximum	621000
Range	621000
Interquartile range (IQR)	3717.25

Descriptive statistics

Standard deviation	15666.15974
Coefficient of variation (CV)	3.246147995
Kurtosis	277.3337677
Mean	4826.076867
Median Absolute Deviation (MAD)	1500
Skewness	12.90498482
Sum	144782306
Variance	245428561.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6408	21.4%
1000	1394	4.6%
2000	1214	4.0%
3000	887	3.0%
5000	810	2.7%
1500	441	1.5%
4000	402	1.3%
10000	341	1.1%
2500	259	0.9%
500	258	0.9%
Other values (6927)	17586	58.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	6408	21.4%
1	22	0.1%
2	22	0.1%
3	13	< 0.1%
4	20	0.1%
5	12	< 0.1%
6	16	0.1%
7	11	< 0.1%
8	7	< 0.1%
9	9	< 0.1%

Value	Count	Frequency (%)
621000	1	< 0.1%
528897	1	< 0.1%
497000	1	< 0.1%
432130	1	< 0.1%
400046	1	< 0.1%
331788	1	< 0.1%
330982	1	< 0.1%
320008	1	< 0.1%
313094	1	< 0.1%
292962	1	< 0.1%

previous_payment_may
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6897
Distinct (%)	23.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4799.387633

Minimum	0
Maximum	426529
Zeros	6703
Zeros (%)	22.3%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	252.5
median	1500
Q3	4031.5
95-th percentile	16000
Maximum	426529
Range	426529
Interquartile range (IQR)	3779

Descriptive statistics

Standard deviation	15278.30568
Coefficient of variation (CV)	3.183386475
Kurtosis	180.0639402
Mean	4799.387633
Median Absolute Deviation (MAD)	1500
Skewness	11.12741705
Sum	143981629
Variance	233426624.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6703	22.3%
1000	1340	4.5%
2000	1323	4.4%
3000	947	3.2%
5000	814	2.7%
1500	426	1.4%
4000	401	1.3%
10000	343	1.1%
500	250	0.8%
6000	247	0.8%
Other values (6887)	17206	57.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	6703	22.3%
1	21	0.1%
2	13	< 0.1%
3	13	< 0.1%
4	12	< 0.1%
5	9	< 0.1%
6	7	< 0.1%
7	9	< 0.1%
8	6	< 0.1%
9	6	< 0.1%

Value	Count	Frequency (%)
426529	1	< 0.1%
417990	1	< 0.1%
388071	1	< 0.1%
379267	1	< 0.1%
332000	1	< 0.1%
331788	1	< 0.1%
330982	1	< 0.1%
326889	1	< 0.1%
317077	1	< 0.1%
310135	1	< 0.1%

previous_payment_apr
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	6939
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5215.502567

Minimum	0
Maximum	528666
Zeros	7173
Zeros (%)	23.9%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	117.75
median	1500
Q3	4000
95-th percentile	17343.8
Maximum	528666
Range	528666
Interquartile range (IQR)	3882.25

Descriptive statistics

Standard deviation	17777.46578
Coefficient of variation (CV)	3.408581541
Kurtosis	167.1614296
Mean	5215.502567
Median Absolute Deviation (MAD)	1500
Skewness	10.64072733
Sum	156465077
Variance	316038289.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	7173	23.9%
1000	1299	4.3%
2000	1295	4.3%
3000	914	3.0%
5000	808	2.7%
1500	439	1.5%
4000	411	1.4%
10000	356	1.2%
500	247	0.8%
6000	220	0.7%
Other values (6929)	16838	56.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	7173	23.9%
1	20	0.1%
2	9	< 0.1%
3	14	< 0.1%
4	12	< 0.1%
5	7	< 0.1%
6	6	< 0.1%
7	5	< 0.1%
8	6	< 0.1%
9	7	< 0.1%

Value	Count	Frequency (%)
528666	1	< 0.1%
527143	1	< 0.1%
443001	1	< 0.1%
422000	1	< 0.1%
403500	1	< 0.1%
377000	1	< 0.1%
372495	1	< 0.1%
351282	1	< 0.1%
345293	1	< 0.1%
308000	1	< 0.1%

default_payment_next_month
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

0	23364
1	6636

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring characters

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	23364	77.9%
1	6636	22.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	limit_bal	sex	education	marriage	age	payment_status_sep	payment_status_aug	payment_status_jul	payment_status_jun	payment_status_may	payment_status_apr	bill_statement_sep	bill_statement_aug	bill_statement_jul	bill_statement_jun	bill_statement_may	bill_statement_apr	previous_payment_sep	previous_payment_aug	previous_payment_jul	previous_payment_jun	previous_payment_may	previous_payment_apr	default_payment_next_month
0	20000	Female	University	Married	24.0	Payment delayed 2 months	Payment delayed 2 months	Payed duly	Payed duly	Unknown	Unknown	3913	3102	689	0	0	0	0	689	0	0	0	0	1
1	120000	Female	University	Single	26.0	Payed duly	Payment delayed 2 months	Unknown	Unknown	Unknown	Payment delayed 2 months	2682	1725	2682	3272	3455	3261	0	1000	1000	1000	0	2000	1
2	90000	Female	University	Single	34.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	29239	14027	13559	14331	14948	15549	1518	1500	1000	1000	1000	5000	0
3	50000	Female	University	Married	37.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	46990	48233	49291	28314	28959	29547	2000	2019	1200	1100	1069	1000	0
4	50000	Male	University	Married	57.0	Payed duly	Unknown	Payed duly	Unknown	Unknown	Unknown	8617	5670	35835	20940	19146	19131	2000	36681	10000	9000	689	679	0
5	50000	Male	Graduate school	Single	37.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	64400	57069	57608	19394	19619	20024	2500	1815	657	1000	1000	800	0
6	500000	Male	Graduate school	Single	29.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	367965	412023	445007	542653	483003	473944	55000	40000	38000	20239	13750	13770	0
7	100000	Female	University	Single	23.0	Unknown	Payed duly	Payed duly	Unknown	Unknown	Payed duly	11876	380	601	221	-159	567	380	601	0	581	1687	1542	0
8	140000	Female	High school	Married	28.0	Unknown	Unknown	Payment delayed 2 months	Unknown	Unknown	Unknown	11285	14096	12108	12211	11793	3719	3329	0	432	1000	1000	1000	0
9	20000	Male	High school	Single	35.0	Unknown	Unknown	Unknown	Unknown	Payed duly	Payed duly	0	0	0	0	13007	13912	0	0	0	13007	1122	0	0

Last rows

	limit_bal	sex	education	marriage	age	payment_status_sep	payment_status_aug	payment_status_jul	payment_status_jun	payment_status_may	payment_status_apr	bill_statement_sep	bill_statement_aug	bill_statement_jul	bill_statement_jun	bill_statement_may	bill_statement_apr	previous_payment_sep	previous_payment_aug	previous_payment_jul	previous_payment_jun	previous_payment_may	previous_payment_apr	default_payment_next_month
29990	140000	Male	University	Married	41.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	138325	137142	139110	138262	49675	46121	6000	7000	4228	1505	2000	2000	0
29991	210000	Male	University	Married	34.0	Payment delayed 3 months	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	2500	2500	2500	2500	2500	2500	0	0	0	0	0	0	1
29992	10000	Male	High school	Married	43.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	8802	10400	0	0	0	0	2000	0	0	0	0	0	0
29993	100000	Male	Graduate school	Single	38.0	Unknown	Payed duly	Payed duly	Unknown	Unknown	Unknown	3042	1427	102996	70626	69473	55004	2000	111784	4000	3000	2000	2000	0
29994	80000	Male	University	Single	34.0	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 2 months	72557	77708	79384	77519	82607	81158	7000	3500	0	7000	0	4000	1
29995	220000	NaN	High school	Married	39.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	188948	192815	208365	88004	31237	15980	8500	20000	5003	3047	5000	1000	0
29996	150000	Male	High school	Single	43.0	Payed duly	Payed duly	Payed duly	Payed duly	Unknown	Unknown	1683	1828	3502	8979	5190	0	1837	3526	8998	129	0	0	0
29997	30000	Male	University	Single	37.0	Payment delayed 4 months	Payment delayed 3 months	Payment delayed 2 months	Payed duly	Unknown	Unknown	3565	3356	2758	20878	20582	19357	0	0	22000	4200	2000	3100	1
29998	80000	Male	High school	Married	41.0	Payment delayed 1 month	Payed duly	Unknown	Unknown	Unknown	Payed duly	-1645	78379	76304	52774	11855	48944	85900	3409	1178	1926	52964	1804	1
29999	50000	Male	University	Married	46.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	47929	48905	49764	36535	32428	15313	2078	1800	1430	1000	1000	1000	1

Most frequently occurring

	limit_bal	sex	education	marriage	age	payment_status_sep	payment_status_aug	payment_status_jul	payment_status_jun	payment_status_may	payment_status_apr	bill_statement_sep	bill_statement_aug	bill_statement_jul	bill_statement_jun	bill_statement_may	bill_statement_apr	default_payment_next_month	# duplicates
0	20000	Male	University	Single	24.0	Payment delayed 2 months	Payment delayed 2 months	Payment delayed 4 months	Payment delayed 4 months	Payment delayed 4 months	Payment delayed 4 months	1650	1650	1650	1650	1650	1650	1	2
1	50000	Male	University	Single	26.0	Payment delayed 1 month	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
2	80000	Female	High school	Married	42.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
3	80000	Female	University	Married	31.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
4	80000	Female	University	Single	25.0	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
5	90000	Female	Graduate school	Single	31.0	Payment delayed 1 month	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
6	100000	Female	University	Married	49.0	Payment delayed 1 month	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
7	110000	Female	Graduate school	Single	31.0	Payment delayed 1 month	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
8	140000	Male	Graduate school	Single	29.0	Payment delayed 1 month	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2
9	150000	Female	Graduate school	Married	31.0	Payment delayed 1 month	Unknown	Unknown	Unknown	Unknown	Unknown	0	0	0	0	0	0	0	2

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII